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accession-icon GSE45483
HMGA1: A master regulator of tumor progression in triple-negative breast cancer cells
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [transcript (gene) version (huex10st)

Description

Emerging evidence suggests that tumor cells metastasize by co-opting stem cell transcriptional networks, although the molecular underpinnings of this process are poorly understood. Here, we show for the first time that the high mobility group A1 (HMGA1) gene drives metastatic progression in triple negative breast cancer cells (MDA-MB-231) by reprogramming cancer cells to a stem-like state. We discovered an HMGA1 signature in triple negative breast cancer cells that is highly enriched in embryonic stem cells. Together, these findings indicate that HMGA1 is a master regulator of tumor progression in breast cancer by reprogramming cancer cells through stem cell transcriptional networks. Future studies are needed to determine how to target HMGA1 in therapy.

Publication Title

HMGA1: a master regulator of tumor progression in triple-negative breast cancer cells.

Sample Metadata Fields

Specimen part, Cell line

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accession-icon GSE67134
Expression data from KSL and GMP cells of FLT3/ITD and FLT3/ITD-SmoM2 mice
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

FLT3/ITD-SmoM2 mice developed rapidly fatal myeloid leukemia compared to FLT3/ITD only mice, suggesting that overactivation of the Hedgehog signaling pathway via SmoM2 can drive myeloid disease progression

Publication Title

Integration of Hedgehog and mutant FLT3 signaling in myeloid leukemia.

Sample Metadata Fields

Specimen part

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accession-icon GSE77434
Functionally relevant prediction model for colorectal cancer
  • organism-icon Homo sapiens
  • sample-icon 41 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Exon 1.0 ST Array [transcript (gene) version (huex10st)

Description

Filtered selection coupled with support vector machines generate functionally relevant prediction model for colorectal cancer. In this study, we built a model that uses Support Vector Machine (SVM) to classify cancer and normal samples using Affymetrix exon microarray data obtained from 90 samples of 48 patients diagnosed with CRC. From the 22,011 genes, we selected the 20, 30, 50, 100, 200, 300 and 500 genes most relevant to CRC using the Minimum-RedundancyMaximum-Relevance (mRMR) technique. With these gene sets, an SVM model was designed using four different kernel types (linear, polynomial, radial basis function and sigmoid).

Publication Title

Filtered selection coupled with support vector machines generate a functionally relevant prediction model for colorectal cancer.

Sample Metadata Fields

Sex, Age, Specimen part, Disease stage

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accession-icon GSE27626
Responses of Zea mays root tissue to inoculation with the necrotrophic root pathogen Phytophthora cinnamomi
  • organism-icon Zea mays
  • sample-icon 12 Downloadable Samples
  • Technology Badge Icon Affymetrix Maize Genome Array (maize)

Description

Phytophthora cinnamomi is a devastating soil-borne oomycete with a very broad host range however there remains a major gap in the understanding of plant resistance responses to the pathogen, furthermore, necrotrophic plant-pathogen interactions, particularly those of root pathogens, remain poorly understood. Zea mays exhibits non-host resistance to the pathogen and has been well characterised as a model species. Using the maize Affymetrix GeneChip array we conducted genome-wide gene expression profiling to elucidate the defence genes and pathways which are induced in the root tissue of a resistant plant species to the pathogen.

Publication Title

Transcriptional profiling of Zea mays roots reveals roles for jasmonic acid and terpenoids in resistance against Phytophthora cinnamomi.

Sample Metadata Fields

Specimen part, Time

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accession-icon GSE76706
The impact of transgenic Uchl1 on gene expression in germinal center B-cells from ImHABCL6 mice
  • organism-icon Mus musculus
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

This study seeks to understand the mechanisms behind enhanced lymphomagenesis observed in ImHABCL6/Uchl1 mice compared with ImHABCL6 alone. As the lymphomas arise from germinal center (GC) B-cells, we reasoned that transgenic Uchl1 altered the gene expression patterns in GC B-cells from these animals. We therefore isolated pre-malignant GC B-cells and examined the gene expression patterns to identify pathways affected by the addition of Uchl1.

Publication Title

UCH-L1 is induced in germinal center B cells and identifies patients with aggressive germinal center diffuse large B-cell lymphoma.

Sample Metadata Fields

Specimen part

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accession-icon GSE69713
Patterns of gene expression in human fetal and adult liver
  • organism-icon Homo sapiens
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Human Gene 1.0 ST Array (hugene10st)

Description

DNA methylation is an important epigenetic control mechanism that has been shown to be associated with gene silencing through the course of development, maturation and aging. However, only limited data are available regarding the relationship between methylation and gene expression in human development. We analyzed the methylomes and transcriptomes of three human fetal liver samples (gestational age 20-22 weeks) and three adult human liver samples. Genes whose expression differed between fetal and adult numbered 7,673. Adult overexpression was associated with metabolic pathways and, in particular, cytochrome P450 enzymes, while fetal overexpression reflected enrichment for DNA replication and repair. Analysis for DNA methylation using the Illumina Infinium 450K HumanMethylation BeadChip showed that 42% of the quality filtered 426,154 methylation sites differed significantly between adult and fetal tissue (q0.05). Differences were small; 69% of the significant sites differed in their mean methylation beta value by 0.2. There was a trend among all sites toward higher methylation in the adult samples with the most frequent difference in beta being 0.1. Characterization of the relationship between methylation and expression revealed a clear difference between fetus and adult. Methylation of genes overexpressed in fetal liver showed the same pattern as seen for genes that were similarly expressed in fetal and adult liver. In contrast, adult overexpressed genes showed fetal hypermethylation that differed from the similarly expressed genes. An examination of gene region-specific methylation showed that sites proximal to the transcription start site or within the first exon with a significant fetal-adult difference in beta (>0.2) showed an inverse relationship with gene expression. Nearly half of the CpGs in human liver show a significant difference in methylation comparing fetal and adult samples. Sites proximal to the transcription start site or within the first exon that show a transition from hypermethylation in the fetus to hypomethylation or intermediate methylation in the adult are associated with inverse changes in gene expression. In contrast, increases in methylation going from fetal to adult are not associated with fetal-to-adult decreased expression. These findings indicate fundamentally different roles for and/or regulation of DNA methylation in human fetal and adult liver.

Publication Title

Patterns of gene expression and DNA methylation in human fetal and adult liver.

Sample Metadata Fields

Sex, Age, Specimen part

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accession-icon GSE17867
Metabolically engineered urea degrading and urea importing Sake yeast strains K7 (WT), K7 Dur1,2 and K7 Dur3
  • organism-icon Saccharomyces cerevisiae
  • sample-icon 6 Downloadable Samples
  • Technology Badge Icon Affymetrix Yeast Genome S98 Array (ygs98)

Description

Excess/residual urea is a pervasion problem in wine and Sake fermentation. We sought to reduce residual urea levels (to reduce ethyl carbamate leves) by engineering the Sake yeast strain K7 to constitutively express either the urea amidolyase (Dur1,2) or urea importer (Dur3). We sought to then compare the gene expression profiles of the metabolically engineered yeast strains to the parental strain during fermentation.

Publication Title

Functional enhancement of Sake yeast strains to minimize the production of ethyl carbamate in Sake wine.

Sample Metadata Fields

No sample metadata fields

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accession-icon SRP043108
The human skeletal muscle transcriptome – sex differences, alternative splicing and tissue homogeneity assessed with RNA sequencing
  • organism-icon Homo sapiens
  • sample-icon 79 Downloadable Samples
  • Technology Badge IconIlluminaHiSeq2000

Description

The amount of RNA sequencing data on skeletal muscle is very limited. We have analyzed a large set of human muscle biopsy samples and provide extensive information on the baseline skeletal muscle transcriptome, including completely novel protein-coding transcripts. Overall design: Analyze of transcriptome in 23 skeletal muscle biopsy samples from six individuals. Four biopsies from each subject, two biopsies from each leg (except subject 6 which has only three biopsies in total).

Publication Title

The human skeletal muscle transcriptome: sex differences, alternative splicing, and tissue homogeneity assessed with RNA sequencing.

Sample Metadata Fields

No sample metadata fields

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accession-icon GSE21966
Transcriptional profiling of P. aeruginosa isolated from 3 individuals with cystic fibrosis over time
  • organism-icon Pseudomonas aeruginosa
  • sample-icon 38 Downloadable Samples
  • Technology Badge Icon Affymetrix Pseudomonas aeruginosa Array (paeg1a)

Description

Pseudomonas aeruginosa chronically colonizes the lungs of individuals with CF, where it reaches high cell densities and produces a battery of virulence factors. Upon infection, a single strain of P. aeruginosa can colonize an individuals lungs throughout his or her lifetime. To understand the evolution of P. aeruginosa during chronic lung infection, we conducted both genotypic and phenotypic analyses on clinical isogenic strains obtained from the lungs of three different individuals with CF. These strains were isolated over a period of approximately ten years and possess phenotypes that are commonly observed in isolates from the CF lung, such as the antibiotic resistant dwarf and mucoid phenotypes. Microarray analyses were carried out on isolates grown in a chemically defined medium that mimics the nutritional environment of the CF lung, synthetic CF sputum medium (SCFM).

Publication Title

Parallel evolution in Pseudomonas aeruginosa over 39,000 generations in vivo.

Sample Metadata Fields

Time

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accession-icon GSE40466
Expression profiling of TGF-beta-induced and hnRNP E1-mediated epithelial-mesenchymal transition
  • organism-icon Mus musculus
  • sample-icon 32 Downloadable Samples
  • Technology Badge Icon Affymetrix Mouse Genome 430 2.0 Array (mouse4302)

Description

Regulation of gene expression at the post-transcriptional level plays an indispensable role during TGFbeta-induced EMT and metastasis. This regulation involves a transcript-selective translational regulatory pathway in which a ribonucleoprotein (mRNP) complex, consisting of heterogeneous nuclear ribonucleoprotein E1 (hnRNP E1) and eukaryotic elongation factor 1A1 (eEF1A1), binds to a 3-UTR regulatory BAT (TGF activated translation) element and silences translation of Dab2 and ILEI mRNAs, two transcripts which are involved in mediating EMT. TGFbeta activates a kinase cascade terminating in the phosphorylation of hnRNP E1, by isoform-specific stimulation of protein kinase B/Akt2, inducing the release of the mRNP complex from the 3-UTR element, resulting in the reversal of translational silencing and increased expression of Dab2 and ILEI transcripts.

Publication Title

Establishment of a TGFβ-induced post-transcriptional EMT gene signature.

Sample Metadata Fields

Specimen part

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refine.bio is a repository of uniformly processed and normalized, ready-to-use transcriptome data from publicly available sources. refine.bio is a project of the Childhood Cancer Data Lab (CCDL)

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Cite refine.bio

Casey S. Greene, Dongbo Hu, Richard W. W. Jones, Stephanie Liu, David S. Mejia, Rob Patro, Stephen R. Piccolo, Ariel Rodriguez Romero, Hirak Sarkar, Candace L. Savonen, Jaclyn N. Taroni, William E. Vauclain, Deepashree Venkatesh Prasad, Kurt G. Wheeler. refine.bio: a resource of uniformly processed publicly available gene expression datasets.
URL: https://www.refine.bio

Note that the contributor list is in alphabetical order as we prepare a manuscript for submission.

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